Evan Paull
Impact in
- Cancer Research top 10%
- Cancer Genomics and Diagnostics
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- Bioinformatics and Genomic Networks
- Gene expression and cancer classification
- Gene Regulatory Network Analysis
Papers in
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- Bioinformatics and Genomic Networks 7
- Gene expression and cancer classification 4
- Melanoma and MAPK Pathways 2
- Gene Regulatory Network Analysis 2
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- Computational Drug Discovery Methods 5
- Co-authors
- Joshua M. Stuart (9 shared papers)Artem Sokolov (3 shared papers)Mario Niepel (3 shared papers)Peter K. Sorger (3 shared papers)David Haussler (1 shared paper)Andrea Califano (6 shared papers)Robert Baertsch (1 shared paper)Yulia Newton (2 shared papers)
- Journals
- Cell (2 papers)Cancer Research (2 papers)Bioinformatics (2 papers)Nature Communications (1 paper)Clinical Cancer Research (1 paper)
- Partner nations
- United StatesSpainChina
In The Last Decade
Evan Paull
17 papers receiving 686 citations
Peers
Comparison fields: 5 of 82
- Cancer Research 156
- Molecular Biology 463
- Computational Theory and Mathematics 68
- Spectroscopy 67
- Biophysics 21
Countries citing papers authored by Evan Paull
This map shows the geographic impact of Evan Paull's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Evan Paull with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Evan Paull more than expected).
Fields of papers citing papers by Evan Paull
This network shows the impact of papers produced by Evan Paull. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Evan Paull. The network helps show where Evan Paull may publish in the future.
Co-authors
The 25 scholars most cited alongside Evan Paull, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 154 | |
| 2 | 2013 | 136 | |
| 3 | 2016 | 76 | |
| 4 | 2017 | 70 | |
| 5 | 2021 | 61 | |
| 6 | 2015 | 57 | |
| 7 | 2018 | 36 | |
| 8 | 2018 | 28 | |
| 9 | 2020 | 20 | |
| 10 | 2020 | 17 | |
| 11 | 2013 | 11 | |
| 12 | 2017 | 10 | |
| 13 | 2017 | 7 | |
| 14 | 2025 | 2 | |
| 15 | 2023 | 2 | |
| 16 | 2016 | 1 | |
| 17 | 2024 | 1 |
About Evan Paull
Evan Paull is a scholar working on Molecular Biology, Computational Theory and Mathematics, Cancer Research, Genetics and Pulmonary and Respiratory Medicine, having authored 17 papers that have together received 689 indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (7 papers), Computational Drug Discovery Methods (5 papers), Gene expression and cancer classification (4 papers), Cancer Genomics and Diagnostics (2 papers), Melanoma and MAPK Pathways (2 papers), Chronic Lymphocytic Leukemia Research (2 papers), Gene Regulatory Network Analysis (2 papers) and Acute Myeloid Leukemia Research (1 paper). The work is most often cited by research in Cancer Research (156 citations), Molecular Biology (463 citations), Computational Theory and Mathematics (68 citations), Spectroscopy (67 citations) and Biophysics (21 citations). Evan Paull has collaborated with scholars based in United States, Spain and China. Frequent co-authors include Joshua M. Stuart, Artem Sokolov, Mario Niepel, Peter K. Sorger, David Haussler, Andrea Califano, Robert Baertsch, Yulia Newton, Christopher K. Wong and Sudha Sud. Their work appears in journals such as Cell, Cancer Research, Bioinformatics, Nature Communications and Clinical Cancer Research.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.